The present invention relates to a technology of personal authentication in which features are obtained from biological information by frequency analysis and personal authentication is performed based on the similarity between the features.
As individual identification techniques using human biological information (biometrics), there have been proposed many methods using information of fingerprints, irises, blood-vessel arrangements in the retinas, faces, and the like. Among these, individual identification using an iris, in particular, is expected to be mainstream of biometrics authentication in the future for the reasons that:                (1) an iris pattern can be acquired with a camera in a noncontact manner,        (2) the false acceptance rate (FAR) is significantly low due to complexity of the iris pattern, and        (3) the iris pattern remains unchanged substantially through the life of the owner.        
Techniques for extracting iris features from iris images and identifying individuals are disclosed in U.S. Pat. No. 5,291,560, Japanese National Phase PCT Laid-Open Publication No. 8-504979, and “High Confidence Visual Recognition of Persons by a Test of Statistical Independence”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 11, November, 1993 (these three disclosures are roughly the same in contents).
In the above techniques, an iris image is analyzed at multiple resolutions using multi-scale self-similarity type two-dimenional quadrature band-pass filters (Gabor filters, for example) to generate a feature (iris code). To state as a specific procedure, a digitized image of a human eye is captured with a video camera, and the boundary between the iris and the sclera and the boundary between the iris and the pupil are determined to separate an iris region from others. A polar coordinate system is applied to the separated iris image, and a plurality of ring analysis bands are determined. Analysis and coding are then performed for the analysis bands using a signal processor comprised of multi-scale quadrature band-pass filters. The thus-generated iris codes are compared with each other by calculating a hamming distance between the codes as shown in FIG. 24, to determine whether or not the compared iris codes originate from an identical person.
Problems to be Solved
The above technique is based on the premise that multi-scale frequency analysis is performed for predetermined fixed frequency bands using an image capture device providing a predetermined fixed resolution in both cases of iris registration and comparison. To fulfill this premise, dedicated registration and authentication devices are necessary.
In view of the recent sophistication in function of cellular phones and personal digital assistants (PDAs), increase in capacity of communication bands, and the like, the following use of personal authentication is considered possible in the near future. That is, a cellular phone or PDA equipped with an image capture device (camera) may be used for taking an iris image of a person and authenticating the person. And this capability may be utilized in occasions of access control, such as logging in to a cellular phone or PDA, authentication in electronic commerce (EC), control of entrance/exit into/from a place requiring physical security, and alternative use to a key of a house. When the above occasions are to be realized, an image capture device incorporated in or mounted externally on a cellular phone or PDA will possibly be comparatively low in resolution at the beginning. In addition, specifications for image capture devices will possibly be different among the types of the devices. Moreover, it is considered that authentication will be effected via a variety of apparatuses such as a terminal mounted on the door, not only a cellular phone and a PDA.
As described above, an iris image may be taken with a variety of apparatuses providing lower to higher resolutions during authentication. Under this situation, if frequency analysis is performed at fixed frequency bands by the conventional method described above, the following problem will arise. That is, when a low-resolution image is input, a part of a feature obtained by analysis at a high frequency (specifically, a frequency component equal to or higher than Fs/2 where Fs is a sampling frequency) is no more useful as the feature. Therefore, if this part obtained by high-frequency analysis is counted as part of the feature, the entire correlation value decreases and thus authentication precision possibly degrades.